CHEMBOND3D e-Module Effectiveness in Enhancing Students’ Knowledge of Chemical Bonding Concept and Visual-spatial Skills

Vui Ket Kuit 1, Kamisah Osman 2 *
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1 Faculty of Education National University of Malaysia 43600 Bangi Selangor, MALAYSIA
2 The National University of Malaysia, MALAYSIA
* Corresponding Author
EUR J SCI MATH ED, Volume 9, Issue 4, pp. 252-264. https://doi.org/10.30935/scimath/11263
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ABSTRACT

Today’s educational challenges necessitate the creative use of digital technology to adapt an effective pedagogical approach in chemistry teaching. While various visualization tools have been developed to improve visual-spatial skills, previous studies on digital technology interventions provide limited findings and show moderate effects on students’ learning. Moreover, students still have misconceptions even after using three-dimensional models physically or virtually while learning chemical bonding. Therefore, this study investigates the effectiveness of the CHEMBOND3D e-module that integrates the web-based visualization tool, Molview, on the chemical bonding concept knowledge and visual-spatial skills between treatment groups and control groups. A pretest-posttest non-equivalent control group with a quasi-experimental quantitative design is used in the research. Pilot studies were conducted to verify the validity and reliability of the CHEMBOND3D Chemical Bonding Knowledge Test and Revised Purdue Visualization Test of Rotations. A total of 112 pre-university students from 10 schools in Sabah were selected based on the sampling method. The findings showed significant improvement in the chemical bonding concept knowledge and visual-spatial skills for treatment group students using CHEMBOND3D e-module compared to control group students using conventional methods. This provides new evidence of the potential of web-based application in learning microscopic chemistry concept in chemical bonding. These findings can facilitate further studies of other digital visualization tools such as virtual reality and augmented reality in support of learning complex chemistry concepts in reaction mechanisms and chemical equilibrium.

CITATION

Kuit, V. K., & Osman, K. (2021). CHEMBOND3D e-Module Effectiveness in Enhancing Students’ Knowledge of Chemical Bonding Concept and Visual-spatial Skills. European Journal of Science and Mathematics Education, 9(4), 252-264. https://doi.org/10.30935/scimath/11263

REFERENCES

  • Abraham, M., Varghese, V., & Tang, H. (2010). Using molecular representations to aid student understanding of stereochemical concepts. Journal of Chemistry Education, 87(12), 1425-1429. https://doi.org/10.1021/ed100497f
  • Al-Balushi, S. M., Al-Musawi, A. S., & Ambusaidi, A. K. (2017). The effectiveness of interacting with scientific animations in chemistry using mobile devices on grade 12 students’ spatial ability and scientific reasoning skills. Journal of Science Educational Technology, 26, 70-81. https://doi.org/10.1007/s10956-016-9652-2
  • Bandura, A. (1977). Social learning theory. Prentice-Hall.
  • Bodner, G. M., & Guay, R. B. (1997). The Purdue visualization of rotations test. The Chemical Educator, 4(2), 1-17. https://doi.org/10.1007/s00897970138a
  • Bodner, G. M., & McMillen, T. L. B. (1986). Cognitive restructuring as an early stage in problem solving. Journal of Research in Science Teaching, 23, 727-737. https://doi.org/10.1002/tea.3660230807
  • Brown, C. E., Whaley, B., & Hyslop, R. M. (2020). Visualizing molecular structures and shapes: A comparison of virtual reality, computer simulation, and traditional modelling. Chemistry Teacher International, 3(1), 1-12. https://doi.org/10.1515/cti-2019-0009
  • Bugaje, B. O. (2013). Qualitative chemistry education: The Role of the teacher. IOSR Journal of Applied Chemistry (IOSR-JAC), 4(5-6), 10-14. https://doi.org/10.9790/5736-0451014
  • Bybee, R. W., Taylor, J. A., Gardner, A., Van Scotter, P., Powell, J., Westbrook, A., & Landes, N. (2006). The BSCS 5E instructional model: Origins and effectiveness. Biological Sciences Curriculum Studies.
  • Che, S. S., Irfan, N. U., Balakrisnan, M., Shakinaz, D., & Hafizul, F. H. (2015). Aplikasi perisian visualisasi tiga dimensi dalam pembelajaran sains biologi: Implikasi terhadap pelajar berbeza keupayaan spatial [Applications of three -dimensional visualization software in biological science learning: Implications for students of different spatial abilities]. Jurnal Pendidikan Sains & Matematik Malaysia, 5(1), 57-69.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). Erlbaum.
  • Craig, P. A., Michel, L. V., & Bateman, R. C. (2013). A survey of educational uses of molecular visualization freeware. Biochemistry and Molecular Biology Education, 41(3), 193-205. https://doi.org/10.1002/bmb.20693
  • Dayang Suryati, A. I., & Mat Rashid, A. (2015). Pengaruh pencapaian akademik dan tahap memori visual jangka pendek terhadap tahap kemahiran visualisasi murid yang mengambil mata pelajaran Lukisan Kejuruteraan [The influence of academic achievement and short -term visual memory level on the level of visualization skills of students taking the subject of Engineering Drawing]. International Journal of Education and Training, 1(2), 1-8.
  • Fatemah, A., Rasool, S., & Habib, U. (2020). Interactive 3D visualization of chemical structure diagrams embedded in text to aid spatial learning process of students. Journal of Chemical Education, 97(4), 992-1000. https://doi.org/10.1021/acs.jchemed.9b00690
  • Ferreira, J. C., & Patino, C. M. (2016). Randomization: Beyond tossing a coin. Jornal Brasileiro de Pneumologia, 42(5), 310. https://doi.org/10.1590/S1806-37562016000000296
  • Gold, A. U., Pendergast, P. M., Ormand, C. J., Budd, D. A., & Mueller, K. J. (2018). Improving spatial thinking skills among undergraduate geology students through short online training exercises. International Journal of Science Education, 40(18), 2205-2225. https://doi.org/10.1080/09500693.2018.1525621
  • Hong, D., & Woo, W. (2006). A framework for virtual reality with tangible augmented reality based user interface. IEICE Transactions on Information and Systems, E89-D(1), 45-52. https://doi.org/10.1093/ietisy/e89-d.1.45
  • Hoyek, N., Collet, C., Di Rienzo, F., De Almeida, M., & Guillot, A. (2014). Effectiveness of three-dimensional digital animation in teaching human anatomy in an authentic classroom context. Anatomical Sciences Education, 7(6), 430-437. https://doi.org/10.1002/ase.1446
  • Ibrahim, D. A., Othman, A., & Talib, O. (2015). Pengajaran dan pembelajaran kimia organik berdasarkan taksonomi Bloom [Teaching and learning organic chemistry based on Bloom’s taxonomy]. Jurnal Pendidikan Bitara UPSI, 9, 12-21.
  • Johari, S., & Yusof, A. (2002). Kesukaran menguasai aras mikroskopik dalam pembinaan konsep sains pelajar [Difficulty mastering the microscopic level in the construction of students ‘science concepts]. Buletin Kimia Universiti Teknologi Malaysia, 31-40.
  • Johnstone, A. H. (1993). The development of chemistry teaching: A changing response to changing demand. Journal of Chemical Education, 70(9), 701-705. https://doi.org/10.1021/ed070p701
  • Karacop, A., & Doymus, K. (2013). Effects of jigsaw cooperative learning and animation techniques on students’ understanding of chemical bonding and their conceptions of the particulate nature of matter. Journal of Science Education and Technology, 22(2), 186-203. https://doi.org/10.1007/s10956-012-9385-9
  • Keehner, M. (2011). Spatial cognition through the keyhole: How studying a real-world domain can inform basic science-and vice versa. Topics in Cognitive Science, 3(4), 632-647. https://doi.org/10.1111/j.1756-8765.2011.01154.x
  • Korakakis, G., Pavlatou, E. A., Palyvos, J. A., & Spyrellis, N. (2009). 3D visualization types in multimedia applications for science learning: A case study for 8th grade students in Greece. Computers & Education, 52(2), 390-401. https://doi.org/10.1016/j.compedu.2008.09.011
  • Koyanagi, K., Fujii, Y., & Furusho, J. (2005). Development of VR-STEF system with force display glove system. In Proceedings of the 15th international conference on Artificial Reality and Telexistence (ICAT2005), (pp. 91-97). Association for Computing Machinery, Christchurch, New Zealand. https://doi.org/10.1145/1152399.1152417
  • Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610. https://doi.org/10.1177/001316447003000308
  • Lohman, D. (1979). Spatial Ability: A Review and Reanalysis of the Correlational Literature. Technical Report No. 8, Aptitiude Research Project. Stanford University, Palo Alto CA.
  • Louca, L. T., & Zachari, Z. C. (2012). Modeling-based learning in science education: cognitive, metacognitive, social, material and epistemological contributions. Educational Review, 64(4), 471-492. https://doi.org/10.1080/00131911.2011.628748
  • Lowe, K. (2004). Interrogation of a dynamic visualization during learning. Learning and Instruction, 14(3), 257-274. https://doi.org/10.1016/j.learninstruc.2004.06.003
  • Martin, W. E., & Bridgmon, K. D. (2012). Quantitative and statistical research methods - from hypothesis to results (Research methods for the social sciences 42). Wiley.
  • Mayer, R. E. (2009). Multimedia learning (2nd Ed.). Cambridge University Press.
  • McCollum, B., Regier, L., Leong, J., Simpson, S., & Sterner, S. (2014). The effects of using touch-screen devices on students’ molecular visualization and representational competence skills. Journal of Chemistry Education, 91(11), 1810-1817. https://doi.org/10.1021/ed400674v
  • Mohamed-Salah, B., & Alain, D. (2016). To what degree does handling concrete molecular models promote the ability to translate and coordinate between 2D and 3D molecular structure representations? A case study with Algerian students. Chemistry Education Research and Practice, 17, 862. https://doi.org/10.1039/C5RP00180C
  • Moore, K. M. (2017). Effects of spatial ability and three-dimensional interactive computer-assisted instruction on functional anatomy (Doctoral thesis). Faculty of Science and Mathematics Education, Florida Institute of Technology, USA.
  • Murray, J. K. (2016). An analysis of first-year engineering majors’ spatial skill. 2016 ASEE Annual Conference & Exposition. American Society for Engineering Education-ASEE. https://doi.org/10.18260/p.26562
  • Narasimha Swamy, K. L., Chavan, P. S., & Murthy, S. (2018). StereoChem: Augmented reality 3D molecular model visualization app for teaching and learning stereochemistry. IEEE 18th International Conference on Advanced Learning Technologies (ICALT), pp. 252-256. https://doi.org/10.1109/ICALT.2018.00065
  • Nechypurenko, P. P., Starova, T. V., Selivanova, T. V., Tomilina, A. O., & Uchitel, A. D. (2018). Use of augmented reality in chemistry education. In A. E. Kiv, & V. N. Soloviev (Eds.), 1st International Workshop on Augmented Reality in Education (AREdu 2018) (pp. 15-23). CEUR-WS. http://ceur-ws.org/Vol-2257/paper02.pdf
  • Noraini, I. (2015). Penyelidikan dalam Pendidikan [Research in education]. McGraw Hill.
  • Okorie, E. U., Agah, J. J., Orakwe, C. U., & Oyiga, F. K. (2019). Effect of examination and teaching curriculum-based scheme of work on secondary school students’ interest and achievement in chemistry. Journal of CUDIMAC (J-CUDIMAC), 6(1), 99-109.
  • Okoye, F. N. (2016). Effects of cooperative and competitive instructional techniques on students’ achievement and interest in geometry in Aguata education zone in Anambra State (Unpublished master’s degree). Department of Science Education, University of Nigeria, Nsukka.
  • Olimpo, J. T., Kumi, B. C., Wroblewski, R., & Dixon, B. L. (2015). Examining the relationship between 2D diagrammatic conventions and students’ success on representational translation tasks in organic chemistry. Chemistry Education Research and Practice, 16, 143-153. https://doi.org/10.1039/C4RP00169A
  • Oliver-Hoyo, M., & Babilonia-Rosa, M. (2017). Promotion of spatial skills in chemistry and biochemistry education at the college level. Journal of Chemistry Education, 94(8), 996-1006. https://doi.org/10.1021/acs.jchemed.7b00094
  • Palmer, D., Stough, L., Burdenski, T, Jr., & Gonzales, M. (2005). Identifying teacher expertise: An examination of researchers’ decision making. Educational Psychologist, 40, 13-25. https://doi.org/10.1207/s15326985ep4001_2
  • Päßler, K., & Hell, B. (2012). Do interests and cognitive abilities help explain college major choice equally well for women and men? Journal of Career Assessment, 20(4), 479-496. https://doi.org/10.1177/1069072712450009
  • Pérez, J. R. B., Pérez, M. E. B., Calatayud, M. L., & Sabater, J. V. (2017). Student’s misconceptions on chemical bonding: A comparative study between high school and first year university students. Asian Journal of Education and e-Learning, 5(1), 1-15.
  • Piaget, J. (1954). The construction of reality in the child. Basic Books. https://doi.org/10.1037/11168-000
  • Rayan, B., & Rayan, A. (2017). Avogadro program for chemistry education: To what extent can molecular visualization and three-dimensional simulations enhance meaningful chemistry learning? World Journal of Chemical Education, 5(4), 136-141. https://doi.org/10.12691/wjce-5-4-4
  • Rose Khairunnisa, R., & Azlina, A. (2017). 3D spatial visualisation skills training application for school students using hologram pyramid. International Journal on Informatics Visualization, 1(4), 170-174. https://doi.org/10.30630/joiv.1.4.61
  • Safadel, P., & White, D. (2020). Effectiveness of computer-generated virtual reality (VR) in learning and teaching environments with spatial frameworks. Applied Sciences, 10(16), 1-17. https://doi.org/10.3390/app10165438
  • Smith, D., & Hardaker, G. (2000). e-Learning innovation through the implementation of an Internet supported learning environment. Journal of Educational Technology & Society, 3, 1-16. https://www.jstor.org/stable/jeductechsoci.3.3.422
  • Sung, Y., Chang, K., & Liu, T. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis. Computers & Education, 94, 252-275, https://doi.org/10.1016/j.compedu.2015.11.008
  • Taber, K. S. (2005). Learning quanta: Barriers to stimulating transitions in student understanding of orbital ideas. Science Education, 89(1), 94-116. https://doi.org/10.1002/sce.20038
  • Ulrich, S. (1991). Interest, learning and motivation. Educational Psychology, 26(3&4), 299-323. https://doi.org/10.1080/00461520.1991.9653136
  • Urso, P., & Fisher, L. (2015). Education technology to service a new population of eLearners. International Journal of Childbirth Education, 30(3), 33-36.
  • Uttal, D. H., & Cohen, C. A. (2012). Chapter Four - Spatial thinking and STEM education: When, why, and how? In B. H. Ross (Ed.), The psychology of learning and motivation (vol. 57, pp. 147-181). Elsevier Academic Press. https://doi.org/10.1016/B978-0-12-394293-7.00004-2
  • Wu, H. K., & Shah, P. (2004). Exploring visuospatial thinking in chemistry learning. Research in Science Education, 88(3), 465-492. https://doi.org/10.1002/sce.10126
  • Yang, E. M., Andre, T., & Greenbowe, T. J. (2003). Spatial ability and the impact of visualization and animation on learning electrochemistry. International Journal of Science Education, 25(3), 329-349. https://doi.org/10.1080/09500690210126784
  • Yoon, S. Y. (2001). Psychometric properties of the Revised Purdue Spatial Visualization Tests: Visualization of rotations (The Revised PSVT:R). ProQuest LLC.